Revert inputs

app.py

@@ -32,9 +32,6 @@ def generate_content(
     transformation,
     num_inference_steps,
     seed,
-    guidance_scale,
-    noise_level,
-    reduction,
 ):
     prompts = [f'{style} {p}'.strip() for p in [prompt_for_original, prompt_for_transformed]]
     prompt_embeds = [stage_1.encode_prompt(p) for p in prompts]
@@ -53,9 +50,7 @@ def generate_content(
                            negative_prompt_embeds,
                            views,
                            num_inference_steps=num_inference_steps,
-                           generator=generator,
-                           guidance_scale=guidance_scale,
-                           reduction=reduction)
+                           generator=generator)
 
     print("Sample stage 2")
     image = sample_stage_2(stage_2,
@@ -64,10 +59,7 @@ def generate_content(
                            negative_prompt_embeds,
                            views,
                            num_inference_steps=num_inference_steps,
-                           generator=generator,
-                           guidance_scale=guidance_scale,
-                           noise_level=noise_level,
-                           reduction=reduction)
+                           generator=generator)
     save_illusion(image, views, Path(""))
     
     output_name = f"illusion.mp4"
@@ -94,11 +86,8 @@ gradio_app = gr.Interface(
         gr.Textbox(label="Prompt for original view", placeholder="a dress"),
         gr.Textbox(label="Prompt for transformed view", placeholder="an old man"),
         gr.Dropdown(label="View transformation", choices=choices, value=choices[0]),
-        gr.Number(label="Number of diffusion steps", value=75, step=1, minimum=1, maximum=300),
+        gr.Number(label="Number of diffusion steps", value=30, step=1, minimum=1, maximum=300),
         gr.Number(label="Random seed", value=0, step=1, minimum=0, maximum=100000),
-        gr.Number(label="Guidance scale", value=7, step=1, minimum=1, maximum=10, info="How strongly diffusion is guided by the prompts"),
-        gr.Number(label="Noise level", value=50, step=1, minimum=1, maximum=100, info="Noise level for stage 2 of diffusion sampling", visible=False),
-        gr.Dropdown(label="Reduction", choices=["mean", "alternate"], value="mean", info="Method for reducing predicted noise and variances", visible=False),
     ],
     outputs=[gr.Video(label="Illusion"), gr.Image(label="Before and After")],
     description=description,